Abstract
Prediction of the time series of relativistic electrons flux in the outer radiation belt of the Earth is a complicated task, due to complexity and nonlinearity of the system “solar wind - the Earth’s magnetosphere”. However, using artificial neural networks it is possible to predict the value of the electron flux several hours ahead, based on the hourly time series of electron flux, parameters of solar wind and interplanetary magnetic field. The purpose of this study was to check, which approach provided higher precision of prediction with various horizons from one to twelve hours: autonomous prediction for each of the 12 prediction horizons, or simultaneous prediction for several horizons. An explanation of the obtained results is suggested.
This study was supported by RFBR grant no. 14-01-00293-a.
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Myagkova, I., Shiroky, V., Dolenko, S. (2016). Effect of Simultaneous Time Series Prediction with Various Horizons on Prediction Quality at the Example of Electron Flux in the Outer Radiation Belt of the Earth. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_38
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